Technical Field
The embodiments herein generally relate to video production systems, and more particularly to automatically generating notes and classifying multimedia content specific to a video production using a video production system.
Description of the Related Art
With the falling costs and increased ease of use of advanced digital video recording technology, professional film and video producers, directors, and editors are flooded with more video content than ever before. Even a short duration feature film (e.g., a 90 minute feature film) may have hours of production video content with (i) multiple camera angles and subjects, and (ii) multiple data. This can be extremely expensive and time consuming to manage and catalog video content for a production, which takes place over many months or even years. Even with a well-organized video management process, producers, directors, and editors often struggle and waste time searching for a particular video content for a story or scene, often relying on their memories and notes.
It further becomes difficult to manage the video content being produced when multiple camera angles must be cataloged and synchronized with multiple separate audio feeds from boom microphones and lavaliere microphones which may be wireless and monitored by a sound engineer or by camera operators. The problem further arises for the video content management in a consumer field as most people capture and archive more video content from settings over a lifetime. This becomes even harder for users of that content to find exactly what they are looking for.
Video content management systems that are already in the market allow users to organize content with consistent naming conventions, and organize file folders around one or more topics. There are a few editing systems that allow users to manually add notes to video and audio files. However, the fundamental problem with such systems is that folders only have one dimension, and video files are in one folder around one topic or are replicated across many folders with subsequently many other topics creating an explosion of content and a version control hazard.
Other attempts have been made to analyze and search the video images for subjects, objects, and other features using facial recognition or subject and object recognition software approaches. These approaches are imprecise and can lead to missing or misclassifying important subjects, while still not capturing important attributes that might be needed by the producer. Accordingly, there remains a need for accurately annotating multimedia content with useful and accurate data, and automatically classifying one or more sections in the annotated multimedia content, thus allowing users of the annotated multimedia content being classified to quickly and accurately organize and search for a specific content based on a wide variety of features.